Flexible Sensorimotor Computations through Rapid Reconfiguration of Cortical Dynamics

Neural mechanisms that support flexible sensorimotor computations are not well understood. In a dynamical system whose state is determined by interactions among neurons, computations can be rapidly reconfigured by controlling the system’s inputs and initial conditions. To investigate whether the bra...

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Published inNeuron (Cambridge, Mass.) Vol. 98; no. 5; pp. 1005 - 1019.e5
Main Authors Remington, Evan D., Narain, Devika, Hosseini, Eghbal A., Jazayeri, Mehrdad
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 06.06.2018
Elsevier Limited
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Online AccessGet full text
ISSN0896-6273
1097-4199
1097-4199
DOI10.1016/j.neuron.2018.05.020

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Summary:Neural mechanisms that support flexible sensorimotor computations are not well understood. In a dynamical system whose state is determined by interactions among neurons, computations can be rapidly reconfigured by controlling the system’s inputs and initial conditions. To investigate whether the brain employs such control mechanisms, we recorded from the dorsomedial frontal cortex of monkeys trained to measure and produce time intervals in two sensorimotor contexts. The geometry of neural trajectories during the production epoch was consistent with a mechanism wherein the measured interval and sensorimotor context exerted control over cortical dynamics by adjusting the system’s initial condition and input, respectively. These adjustments, in turn, set the speed at which activity evolved in the production epoch, allowing the animal to flexibly produce different time intervals. These results provide evidence that the language of dynamical systems can be used to parsimoniously link brain activity to sensorimotor computations. [Display omitted] •Monkeys performed a timing task demanding flexible cognitive control•The organization of neural trajectories in frontal cortex reflected task demands•Flexible control was best explained in terms of inputs and initial conditions•Recurrent neural network models validated the inferred control principles Remington et al. employ a dynamical systems perspective to understand how the brain flexibly controls timed movements. Results suggest that neurons in the frontal cortex form a recurrent network whose behavior is flexibly controlled by inputs and initial conditions.
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ISSN:0896-6273
1097-4199
1097-4199
DOI:10.1016/j.neuron.2018.05.020